# README FILE
# Linguistic Assimilation Does Not Reduce Discrimination Against Immigrants: Evidence from Germany
# Donghyun Danny Choi, Mathias Poertner, and Nicholas Sambanis
# Journal of Experimental Political Science
# Date: May 8, 2020


* Replication Files
1. data1.csv: raw experimental data from experiment 1 (required to run DataCleaning_Language.R)
2. data2.csv: raw experimetnal data from experiment 2 (required to run DataCleaning_Language.R)
3. merged.RData: cleaned, merged data set from running DataCleaning_Language.R 
4. maps/StationList_east.csv: List of train stations in East Germany used to generate map of study sites in SI Appendix
5. maps/StationList_west.csv: List of train stations in West Germany used to generate map of study sites in SI Appendix
6. maps/DEU_adm1.cpg/dbf/prj/shp/shx: Shape files for map of study sites in SI Appendix
7. mcheck.csv: file from the manipulation check survey analyzed in the SI Appendix


* Cleaning and Analysis Code

Please execute the R code files in the following order:
1. DataCleaning_Language.R: Cleans data and creates key treatment indicators for analysis. Outputs analysis data set merged.RData.
2. DataAnalysis_Language.R: Runs analysis to generate figures and tables included in the main paper.
3. DataAnalysis_Lang_Appendix.R: Runs analysis to generate figures and tables included in the SI Appendix.


* Codebook key variables

1. In data1.csv and data2.csv: base variables

"help"/"anyhelp": main outcome for analysis, codes whether *any* individual helped during an iteration
"trtype": raw treatment indicator, examine comments in DataCleaning_Language.R to identify treatment conditions relevant for analysis.
"bystander": number of bystanders at the iteration level. For data1.csv, some values are not integers, because took the average reported across two independent coders if there was a discrepancy in the number reported by them.
"hpprop": proportion of bystanders with headphones
"team": identifier for the team that implemented the iteration
"femprop": proportion of female bystanders, some values missing for data1.csv
"temp": temperature during the iteration, some values missing
"rush": whether the iteration was conducted during rush hour.


2. In merged.RData: please reference the comments in DataCleaning_Language.R and DataAnalysis_Language.R for explanations on new variables generated




